Chatter about an AI bubble has been everywhere lately, and top tech companies like Google, Meta, and Microsoft have doubled down on their AI investments for 2026. But how have analysts in the past accurately identified forming tech bubbles? Hosts Michael Calore and Lauren Goode sit down with Brian Merchant, WIRED contributor and author of the newsletter Blood in the Machine, to break down the four criteria some researchers have used in the past to understand and brace for the worst.
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You can follow Michael Calore on Bluesky at @snackfight and Lauren Goode on Bluesky at @laurengoode. Write to us at uncannyvalley@wired.com.
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Transcript
Note: This is an automated transcript, which may contain errors.
Michael Calore: Hey Lauren, how are you doing?
Lauren Goode: I’m OK, Mike. It’s earnings season, so a lot of us on the business desk here at WIRED have been tuning into tech companies earnings reports and their earnings calls. And I guess that basically means it’s CapEx season.
Michael Calore: CapEx?
Lauren Goode: Capital expenditures.
Michael Calore: You say CapEx?
Lauren Goode: Yeah. Now that I’m a business desk reporter, I say CapEx.
Michael Calore: You’re one of those.
Lauren Goode: I throw it around at parties. No, I really don’t. But we are seeing a trend in how tech companies are sleeping on piles of money, but they aren’t just sleeping on it. They’re sharing big plans to spend on it, and especially to spend on AI infrastructure.
Michael Calore: Right. Data centers.
Lauren Goode: Yeah, more data centers, not just data centers. But yes, that’s a big part of it.
